Casual Stereoscopic Panorama Stitching

Fan Zhang, Feng Liu; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 2002-2010


This paper presents a method for stitching stereoscopic panoramas from stereo images casually taken using a stereo camera. This method addresses three challenges of stereoscopic image stitching: how to handle parallax, how to stitch the left- and right-view panorama consistently, and how to take care of disparity during stitching. This method addresses these challenges using a three-step approach. First, we employ a state-of-the-art stitching algorithm that handles parallax well to stitch the left views of input stereo images and create the left view of the final stereoscopic panorama. Second, we stitch the input disparity maps to obtain the target disparity map for the stereoscopic panorama by solving a Poisson's equation. This target disparity map is optimized such that there are no vertical disparities and the original perceived depth distribution is preserved. Finally, we warp the right views of the input stereo images and stitch them into the right view of the final stereoscopic panorama according to the target disparity map. The stitching of the right views is formulated as a labeling problem that is constrained by the stitching of the left views to make the left- and right-view panorama consistent to avoid retinal rivalry. Our experiments show that our method can effectively stitch casually taken stereo images and produce high-quality stereoscopic panoramas that deliver a pleasant stereoscopic 3D viewing experience.

Related Material

author = {Zhang, Fan and Liu, Feng},
title = {Casual Stereoscopic Panorama Stitching},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}